Langmuir模型为强化混凝过程中总有机碳（TOC）的全面去除提供了最佳可用预测。由于与处理厂相比，jar测试允许更多的二氧化碳气体转移，因此该模型甚至可以纠正此类测试中出现的某些错误。当模型适用于预测以不同比例混合在一起的两个原水水源中的TOC去除率时，对于一个公用事业公司两年的jar试验数据，标准误差仅为0.15 mg/L。对27家大型公用事业公司的案例研究表明，通过混凝可以准确预测TOC的去除:在一系列使用明矾、三价铁或聚合氯化铝混凝剂的公用事业公司；在长时间内无需频繁重新校准；使用预测而非测量的凝固pH值；对于两个不同比例混合的原水源。包括18个参考文献、表格、图表。

A Langmuir model provides the best available prediction of full-scale removal of total organic carbon (TOC) during enhanced coagulation. Because jar tests allow more transfer of carbon dioxide gas than treatment plants, the model can even correct certain errors arising during such tests. When the model was adapted to predicting TOC removal in two raw water sources mixed together in different proportions, standard error was only 0.15 mg/L for two years of jar-test data at one utility. Case studies of 27 full-scale utilities showed accurate prediction of TOC removal by coagulation: at a range of utilities using alum, ferric, or polyaluminum chloride coagulants; over long time periods without a need for frequent recalibration; with use of a predicted rather than measured coagulation pH; and, for two raw water sources mixed in various proportions. Includes 18 references, tables, figures.